Zobrazeno 1 - 10
of 224
pro vyhledávání: '"Yang Jiansheng"'
Publikováno v:
Measurement Science Review, Vol 23, Iss 1, Pp 40-46 (2023)
Equivalence ratio (Φ) is one of the most important parameters in combustion diagnostics. In previous studies, flame color characteristics have been widely applied to model the Φ of premixed hydrocarbon flames. The flame spatial characteristics also
Externí odkaz:
https://doaj.org/article/a4208c5ad02f4010b55da59d84ee9641
Publikováno v:
Measurement Science Review, Vol 22, Iss 3, Pp 122-135 (2022)
Flame combustion diagnostics is a technique that uses different methods to diagnose the flame combustion process and study its physical and chemical basis. As one of the most important parameters of the combustion process, the flame equivalence ratio
Externí odkaz:
https://doaj.org/article/266a36e04f164964bd548ca89680d16f
Adversarial Training (AT) has become arguably the state-of-the-art algorithm for extracting robust features. However, researchers recently notice that AT suffers from severe robust overfitting problems, particularly after learning rate (LR) decay. In
Externí odkaz:
http://arxiv.org/abs/2310.19360
Computing approximate Nash equilibria in multi-player general-sum Markov games is a computationally intractable task. However, multi-player Markov games with certain cooperative or competitive structures might circumvent this intractability. In this
Externí odkaz:
http://arxiv.org/abs/2308.07873
This paper is concerned with the problem of inverse scattering of time-harmonic acoustic plane waves by a two-layered medium with a locally rough interface in 2D. A direct imaging method is proposed to reconstruct the locally rough interface from the
Externí odkaz:
http://arxiv.org/abs/2305.05941
In recent years, contrastive learning achieves impressive results on self-supervised visual representation learning, but there still lacks a rigorous understanding of its learning dynamics. In this paper, we show that if we cast a contrastive objecti
Externí odkaz:
http://arxiv.org/abs/2303.04435
This paper considers the problems of scattering of time-harmonic acoustic waves by a two-layered medium with a non-locally perturbed boundary (called a rough boundary in this paper) in two dimensions, where a Dirichlet or impedance boundary condition
Externí odkaz:
http://arxiv.org/abs/2303.02339
In this paper, we establish new results for the uniform far-field asymptotics of the two-layered Green function (together with its derivatives) in 2D in the frequency domain. To the best of our knowledge, our results are the sharpest yet obtained. Th
Externí odkaz:
http://arxiv.org/abs/2208.00456
Due to the over-smoothing issue, most existing graph neural networks can only capture limited dependencies with their inherently finite aggregation layers. To overcome this limitation, we propose a new kind of graph convolution, called Graph Implicit
Externí odkaz:
http://arxiv.org/abs/2206.14418
Recently, contrastive learning has risen to be a promising approach for large-scale self-supervised learning. However, theoretical understanding of how it works is still unclear. In this paper, we propose a new guarantee on the downstream performance
Externí odkaz:
http://arxiv.org/abs/2203.13457